Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x24e2a0f2be0>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x24e2a1f6cc0>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.2.1
C:\Users\Mezz\Anaconda2\envs\dlnd\lib\site-packages\ipykernel_launcher.py:14: UserWarning: No GPU found. Please use a GPU to train your neural network.
  

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function

    real_inputs = tf.placeholder(tf.float32,
                                 (None, image_width, image_height, image_channels),
                                 name='input_real')
    z_inputs = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
    learning_rate = tf.placeholder(tf.float32, shape=(), name='learning_rate')
    return real_inputs, z_inputs, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [6]:
#GAN constants
k_size = 5
stride = 2
filter_size_01 = 64
filter_size_02 = filter_size_01*2
filter_size_03 = filter_size_01*4

def discriminator(images, reuse=False, alpha=0.2, drop=0.2):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    
    with tf.variable_scope('discriminator', reuse=reuse):
        x1 = tf.layers.conv2d(images, filter_size_01, k_size, stride,
                              padding='same', use_bias=False,
                              kernel_initializer=tf.contrib.layers.xavier_initializer())
        relu1 = tf.maximum(alpha*x1, x1)
        
        x2 = tf.layers.conv2d(images, filter_size_02, k_size, stride,
                              padding='same', use_bias=False,
                              kernel_initializer=tf.contrib.layers.xavier_initializer())
        bn2 = tf.layers.batch_normalization(x2, training=True)
        relu2 = tf.maximum(alpha*bn2, bn2)
        
        x3 = tf.layers.conv2d(images, filter_size_03, k_size, stride,
                              padding='same', use_bias=False,
                              kernel_initializer=tf.contrib.layers.xavier_initializer())
        bn3 = tf.layers.batch_normalization(x3, training=True)
        relu3 = tf.maximum(alpha*bn3, bn3)
        
        flat = tf.reshape(relu3, (-1, 4*4*filter_size_03))
        dropout = tf.layers.dropout(flat, drop, seed=123, training=True)
        logits = tf.layers.dense(dropout, 1,
                                 kernel_initializer=tf.contrib.layers.xavier_initializer())
        out= tf.sigmoid(logits)

    return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [7]:
def generator(z, out_channel_dim, is_train=True, alpha=0.2, drop=0.2):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    with tf.variable_scope('generator', reuse= not is_train):
        x1 = tf.layers.dense(z, 7*7*filter_size_03*2, use_bias=False,
                             kernel_initializer=tf.contrib.layers.xavier_initializer())
        x1 = tf.reshape(x1, (-1, 7, 7, filter_size_03*2))
        x1 = tf.layers.batch_normalization(x1, training=is_train)
        x1 = tf.maximum(alpha*x1, x1)
        
        x2 = tf.layers.conv2d_transpose(x1, filter_size_02*2, k_size, stride,
                                        padding='same', use_bias=False,
                                        kernel_initializer=tf.contrib.layers.xavier_initializer())
        x2 = tf.layers.batch_normalization(x2, training=is_train)
        x2 = tf.maximum(alpha*x2, x2)
        
        x3 = tf.layers.conv2d_transpose(x2, filter_size_01*2, k_size, stride,
                                        padding='same', use_bias=False,
                                        kernel_initializer=tf.contrib.layers.xavier_initializer())
        x3 = tf.layers.batch_normalization(x3, training=is_train)
        x3 = tf.maximum(alpha*x3, x3)
        
        dropout = tf.layers.dropout(x3, drop, seed=123, training=is_train)
        logits = tf.layers.conv2d_transpose(dropout, out_channel_dim, 3, strides=1,
                                            padding='same', use_bias=False,
                                            kernel_initializer=tf.contrib.layers.xavier_initializer())
        out = tf.tanh(logits)
        
        return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [8]:
def model_loss(input_real, input_z, out_channel_dim, alpha=0.2, drop=0.2):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function
    
    g_out = generator(input_z, out_channel_dim, is_train=True, alpha=alpha, drop=drop)
    d_out_real, d_logits_real = discriminator(input_real, reuse=False, alpha=alpha, drop=drop)
    d_out_fake, d_logits_fake = discriminator(g_out, reuse=True, alpha=alpha, drop=drop)
    
    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real,
                                                labels=tf.ones_like(d_out_real*0.9)))
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake,
                                                labels=tf.zeros_like(d_out_fake)))
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake,
                                                labels=tf.ones_like(d_out_fake)))
    d_loss = d_loss_real + d_loss_fake
    
    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [9]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]
    
    t_update = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
    d_update = [opt for opt in t_update if opt.name.startswith('discriminator')]
    g_update = [opt for opt in t_update if opt.name.startswith('generator')]
    
    with tf.control_dependencies(d_update):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
    
    with tf.control_dependencies(g_update):
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
    
    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [10]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode, alpha, drop):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False, alpha=alpha, drop=drop),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [11]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    
    alpha = 0.15
    drop = 0.3
    _, img_width, img_height, img_channels = data_shape
    input_real, input_z, lr = model_inputs(img_width, img_height,
                                                      img_channels, z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, img_channels, alpha=alpha, drop=drop)
    d_opt, g_opt = model_opt(d_loss, g_loss, lr, beta1)
    
    current_step = 0
    n_images = 25
    print_every = 20
    show_every = 100
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                current_step += 1
                batch_images *= 2.0
                z_noise = np.random.uniform(-1, 1, (batch_size, z_dim))
                
                _ = sess.run(d_opt, feed_dict={input_real: batch_images,
                                               input_z: z_noise,
                                               lr: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_z: z_noise,
                                               lr: learning_rate})
                
                if current_step % print_every == 0:
                    d_train_loss = d_loss.eval({input_z: z_noise,
                                                input_real: batch_images})
                    g_train_loss = g_loss.eval({input_z: z_noise})
                    
                    print('Epoch {}/{}...'.format(epoch_i+1, epoch_count),
                         'Discriminator Loss: {:.4f}...'.format(d_train_loss),
                         'Generator Loss: {:.4f}'.format(g_train_loss))
                    
                if current_step % show_every == 0:
                    show_generator_output(sess, n_images, input_z,
                                          img_channels, data_image_mode, alpha=alpha, drop=0.0)
                

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [13]:
batch_size = 16
z_dim = 128
learning_rate = 0.0002
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 1.4977... Generator Loss: 0.6063
Epoch 1/2... Discriminator Loss: 1.7572... Generator Loss: 0.4439
Epoch 1/2... Discriminator Loss: 0.8049... Generator Loss: 1.5664
Epoch 1/2... Discriminator Loss: 0.7098... Generator Loss: 1.8233
Epoch 1/2... Discriminator Loss: 0.4019... Generator Loss: 2.1253
Epoch 1/2... Discriminator Loss: 0.9711... Generator Loss: 1.2026
Epoch 1/2... Discriminator Loss: 0.9286... Generator Loss: 1.2306
Epoch 1/2... Discriminator Loss: 1.1748... Generator Loss: 0.9096
Epoch 1/2... Discriminator Loss: 2.0102... Generator Loss: 0.4130
Epoch 1/2... Discriminator Loss: 1.2431... Generator Loss: 0.7156
Epoch 1/2... Discriminator Loss: 1.0517... Generator Loss: 0.9805
Epoch 1/2... Discriminator Loss: 1.5352... Generator Loss: 0.7323
Epoch 1/2... Discriminator Loss: 1.3381... Generator Loss: 0.8758
Epoch 1/2... Discriminator Loss: 1.3004... Generator Loss: 0.8605
Epoch 1/2... Discriminator Loss: 1.3474... Generator Loss: 0.7864
Epoch 1/2... Discriminator Loss: 1.3056... Generator Loss: 0.7955
Epoch 1/2... Discriminator Loss: 1.2413... Generator Loss: 0.8331
Epoch 1/2... Discriminator Loss: 1.1897... Generator Loss: 0.9058
Epoch 1/2... Discriminator Loss: 1.3185... Generator Loss: 0.7957
Epoch 1/2... Discriminator Loss: 1.2847... Generator Loss: 0.8396
Epoch 1/2... Discriminator Loss: 1.2857... Generator Loss: 0.7922
Epoch 1/2... Discriminator Loss: 1.2990... Generator Loss: 0.7624
Epoch 1/2... Discriminator Loss: 1.4074... Generator Loss: 0.7843
Epoch 1/2... Discriminator Loss: 1.4402... Generator Loss: 0.7227
Epoch 1/2... Discriminator Loss: 1.4079... Generator Loss: 0.7332
Epoch 1/2... Discriminator Loss: 1.4008... Generator Loss: 0.7525
Epoch 1/2... Discriminator Loss: 1.3407... Generator Loss: 0.8089
Epoch 1/2... Discriminator Loss: 1.3133... Generator Loss: 0.7413
Epoch 1/2... Discriminator Loss: 1.4002... Generator Loss: 0.7544
Epoch 1/2... Discriminator Loss: 1.4053... Generator Loss: 0.8076
Epoch 1/2... Discriminator Loss: 1.3706... Generator Loss: 0.7494
Epoch 1/2... Discriminator Loss: 1.3536... Generator Loss: 0.7334
Epoch 1/2... Discriminator Loss: 1.3699... Generator Loss: 0.7234
Epoch 1/2... Discriminator Loss: 1.3757... Generator Loss: 0.7544
Epoch 1/2... Discriminator Loss: 1.4255... Generator Loss: 0.7539
Epoch 1/2... Discriminator Loss: 1.4008... Generator Loss: 0.7770
Epoch 1/2... Discriminator Loss: 1.4387... Generator Loss: 0.6797
Epoch 1/2... Discriminator Loss: 1.4022... Generator Loss: 0.7385
Epoch 1/2... Discriminator Loss: 1.3794... Generator Loss: 0.7768
Epoch 1/2... Discriminator Loss: 1.3374... Generator Loss: 0.7721
Epoch 1/2... Discriminator Loss: 1.4422... Generator Loss: 0.6496
Epoch 1/2... Discriminator Loss: 1.3491... Generator Loss: 0.7928
Epoch 1/2... Discriminator Loss: 1.3440... Generator Loss: 0.7322
Epoch 1/2... Discriminator Loss: 1.4370... Generator Loss: 0.7126
Epoch 1/2... Discriminator Loss: 1.3959... Generator Loss: 0.7095
Epoch 1/2... Discriminator Loss: 1.4491... Generator Loss: 0.7308
Epoch 1/2... Discriminator Loss: 1.4139... Generator Loss: 0.7569
Epoch 1/2... Discriminator Loss: 1.4306... Generator Loss: 0.6880
Epoch 1/2... Discriminator Loss: 1.3811... Generator Loss: 0.6963
Epoch 1/2... Discriminator Loss: 1.3638... Generator Loss: 0.6877
Epoch 1/2... Discriminator Loss: 1.4136... Generator Loss: 0.7341
Epoch 1/2... Discriminator Loss: 1.3354... Generator Loss: 0.7426
Epoch 1/2... Discriminator Loss: 1.3795... Generator Loss: 0.7186
Epoch 1/2... Discriminator Loss: 1.3946... Generator Loss: 0.7304
Epoch 1/2... Discriminator Loss: 1.4204... Generator Loss: 0.7542
Epoch 1/2... Discriminator Loss: 1.3561... Generator Loss: 0.7281
Epoch 1/2... Discriminator Loss: 1.4161... Generator Loss: 0.7109
Epoch 1/2... Discriminator Loss: 1.3878... Generator Loss: 0.7149
Epoch 1/2... Discriminator Loss: 1.3815... Generator Loss: 0.7265
Epoch 1/2... Discriminator Loss: 1.4323... Generator Loss: 0.6878
Epoch 1/2... Discriminator Loss: 1.4041... Generator Loss: 0.7108
Epoch 1/2... Discriminator Loss: 1.4247... Generator Loss: 0.7027
Epoch 1/2... Discriminator Loss: 1.4284... Generator Loss: 0.7691
Epoch 1/2... Discriminator Loss: 1.3966... Generator Loss: 0.6682
Epoch 1/2... Discriminator Loss: 1.3904... Generator Loss: 0.7371
Epoch 1/2... Discriminator Loss: 1.3562... Generator Loss: 0.7561
Epoch 1/2... Discriminator Loss: 1.4013... Generator Loss: 0.7187
Epoch 1/2... Discriminator Loss: 1.3778... Generator Loss: 0.6974
Epoch 1/2... Discriminator Loss: 1.4174... Generator Loss: 0.7321
Epoch 1/2... Discriminator Loss: 1.3791... Generator Loss: 0.7339
Epoch 1/2... Discriminator Loss: 1.3626... Generator Loss: 0.7291
Epoch 1/2... Discriminator Loss: 1.4114... Generator Loss: 0.7368
Epoch 1/2... Discriminator Loss: 1.3757... Generator Loss: 0.7181
Epoch 1/2... Discriminator Loss: 1.3721... Generator Loss: 0.6720
Epoch 1/2... Discriminator Loss: 1.3811... Generator Loss: 0.6998
Epoch 1/2... Discriminator Loss: 1.4013... Generator Loss: 0.7300
Epoch 1/2... Discriminator Loss: 1.4094... Generator Loss: 0.7442
Epoch 1/2... Discriminator Loss: 1.4167... Generator Loss: 0.7421
Epoch 1/2... Discriminator Loss: 1.4211... Generator Loss: 0.7106
Epoch 1/2... Discriminator Loss: 1.4195... Generator Loss: 0.6607
Epoch 1/2... Discriminator Loss: 1.4358... Generator Loss: 0.7170
Epoch 1/2... Discriminator Loss: 1.4268... Generator Loss: 0.7066
Epoch 1/2... Discriminator Loss: 1.4054... Generator Loss: 0.7114
Epoch 1/2... Discriminator Loss: 1.3825... Generator Loss: 0.7159
Epoch 1/2... Discriminator Loss: 1.4137... Generator Loss: 0.7677
Epoch 1/2... Discriminator Loss: 1.4194... Generator Loss: 0.7525
Epoch 1/2... Discriminator Loss: 1.3824... Generator Loss: 0.7070
Epoch 1/2... Discriminator Loss: 1.3404... Generator Loss: 0.6796
Epoch 1/2... Discriminator Loss: 1.3944... Generator Loss: 0.7382
Epoch 1/2... Discriminator Loss: 1.3785... Generator Loss: 0.7472
Epoch 1/2... Discriminator Loss: 1.4241... Generator Loss: 0.7209
Epoch 1/2... Discriminator Loss: 1.3447... Generator Loss: 0.6790
Epoch 1/2... Discriminator Loss: 1.3818... Generator Loss: 0.7226
Epoch 1/2... Discriminator Loss: 1.4300... Generator Loss: 0.7256
Epoch 1/2... Discriminator Loss: 1.3932... Generator Loss: 0.6718
Epoch 1/2... Discriminator Loss: 1.4078... Generator Loss: 0.6922
Epoch 1/2... Discriminator Loss: 1.3640... Generator Loss: 0.7346
Epoch 1/2... Discriminator Loss: 1.3971... Generator Loss: 0.7295
Epoch 1/2... Discriminator Loss: 1.3956... Generator Loss: 0.7107
Epoch 1/2... Discriminator Loss: 1.3443... Generator Loss: 0.7221
Epoch 1/2... Discriminator Loss: 1.3522... Generator Loss: 0.6749
Epoch 1/2... Discriminator Loss: 1.3537... Generator Loss: 0.6996
Epoch 1/2... Discriminator Loss: 1.3879... Generator Loss: 0.7151
Epoch 1/2... Discriminator Loss: 1.3815... Generator Loss: 0.6913
Epoch 1/2... Discriminator Loss: 1.3608... Generator Loss: 0.7155
Epoch 1/2... Discriminator Loss: 1.3798... Generator Loss: 0.7291
Epoch 1/2... Discriminator Loss: 1.3783... Generator Loss: 0.6761
Epoch 1/2... Discriminator Loss: 1.3726... Generator Loss: 0.7013
Epoch 1/2... Discriminator Loss: 1.3973... Generator Loss: 0.7656
Epoch 1/2... Discriminator Loss: 1.4050... Generator Loss: 0.7964
Epoch 1/2... Discriminator Loss: 1.4006... Generator Loss: 0.7107
Epoch 1/2... Discriminator Loss: 1.3517... Generator Loss: 0.7597
Epoch 1/2... Discriminator Loss: 1.3985... Generator Loss: 0.6949
Epoch 1/2... Discriminator Loss: 1.3632... Generator Loss: 0.7022
Epoch 1/2... Discriminator Loss: 1.3800... Generator Loss: 0.7407
Epoch 1/2... Discriminator Loss: 1.3647... Generator Loss: 0.7371
Epoch 1/2... Discriminator Loss: 1.3703... Generator Loss: 0.6957
Epoch 1/2... Discriminator Loss: 1.3842... Generator Loss: 0.7071
Epoch 1/2... Discriminator Loss: 1.3441... Generator Loss: 0.7631
Epoch 1/2... Discriminator Loss: 1.4030... Generator Loss: 0.6901
Epoch 1/2... Discriminator Loss: 1.3783... Generator Loss: 0.7162
Epoch 1/2... Discriminator Loss: 1.3976... Generator Loss: 0.7240
Epoch 1/2... Discriminator Loss: 1.3743... Generator Loss: 0.7284
Epoch 1/2... Discriminator Loss: 1.3789... Generator Loss: 0.7575
Epoch 1/2... Discriminator Loss: 1.3889... Generator Loss: 0.7035
Epoch 1/2... Discriminator Loss: 1.3866... Generator Loss: 0.6919
Epoch 1/2... Discriminator Loss: 1.3796... Generator Loss: 0.7049
Epoch 1/2... Discriminator Loss: 1.3928... Generator Loss: 0.7187
Epoch 1/2... Discriminator Loss: 1.3923... Generator Loss: 0.7040
Epoch 1/2... Discriminator Loss: 1.3927... Generator Loss: 0.7098
Epoch 1/2... Discriminator Loss: 1.3633... Generator Loss: 0.7621
Epoch 1/2... Discriminator Loss: 1.4277... Generator Loss: 0.6952
Epoch 1/2... Discriminator Loss: 1.4042... Generator Loss: 0.6866
Epoch 1/2... Discriminator Loss: 1.3809... Generator Loss: 0.6845
Epoch 1/2... Discriminator Loss: 1.3986... Generator Loss: 0.7322
Epoch 1/2... Discriminator Loss: 1.4086... Generator Loss: 0.7130
Epoch 1/2... Discriminator Loss: 1.3798... Generator Loss: 0.7053
Epoch 1/2... Discriminator Loss: 1.3796... Generator Loss: 0.7156
Epoch 1/2... Discriminator Loss: 1.3807... Generator Loss: 0.7046
Epoch 1/2... Discriminator Loss: 1.4065... Generator Loss: 0.7008
Epoch 1/2... Discriminator Loss: 1.3689... Generator Loss: 0.7372
Epoch 1/2... Discriminator Loss: 1.3765... Generator Loss: 0.7303
Epoch 1/2... Discriminator Loss: 1.4134... Generator Loss: 0.6790
Epoch 1/2... Discriminator Loss: 1.4002... Generator Loss: 0.7285
Epoch 1/2... Discriminator Loss: 1.3816... Generator Loss: 0.6951
Epoch 1/2... Discriminator Loss: 1.3482... Generator Loss: 0.6970
Epoch 1/2... Discriminator Loss: 1.3866... Generator Loss: 0.6982
Epoch 1/2... Discriminator Loss: 1.3912... Generator Loss: 0.6839
Epoch 1/2... Discriminator Loss: 1.4167... Generator Loss: 0.7040
Epoch 1/2... Discriminator Loss: 1.3922... Generator Loss: 0.7343
Epoch 1/2... Discriminator Loss: 1.3926... Generator Loss: 0.6714
Epoch 1/2... Discriminator Loss: 1.3676... Generator Loss: 0.7349
Epoch 1/2... Discriminator Loss: 1.3650... Generator Loss: 0.7088
Epoch 1/2... Discriminator Loss: 1.4190... Generator Loss: 0.7177
Epoch 1/2... Discriminator Loss: 1.4174... Generator Loss: 0.7052
Epoch 1/2... Discriminator Loss: 1.4240... Generator Loss: 0.6948
Epoch 1/2... Discriminator Loss: 1.3907... Generator Loss: 0.6839
Epoch 1/2... Discriminator Loss: 1.3990... Generator Loss: 0.6927
Epoch 1/2... Discriminator Loss: 1.4023... Generator Loss: 0.7278
Epoch 1/2... Discriminator Loss: 1.3405... Generator Loss: 0.6863
Epoch 1/2... Discriminator Loss: 1.3838... Generator Loss: 0.7429
Epoch 1/2... Discriminator Loss: 1.3836... Generator Loss: 0.7135
Epoch 1/2... Discriminator Loss: 1.3805... Generator Loss: 0.6756
Epoch 1/2... Discriminator Loss: 1.3764... Generator Loss: 0.6853
Epoch 1/2... Discriminator Loss: 1.3578... Generator Loss: 0.6971
Epoch 1/2... Discriminator Loss: 1.3915... Generator Loss: 0.6925
Epoch 1/2... Discriminator Loss: 1.4260... Generator Loss: 0.6918
Epoch 1/2... Discriminator Loss: 1.3730... Generator Loss: 0.7088
Epoch 1/2... Discriminator Loss: 1.3770... Generator Loss: 0.7123
Epoch 1/2... Discriminator Loss: 1.4085... Generator Loss: 0.6859
Epoch 1/2... Discriminator Loss: 1.3854... Generator Loss: 0.6829
Epoch 1/2... Discriminator Loss: 1.3564... Generator Loss: 0.7239
Epoch 1/2... Discriminator Loss: 1.4113... Generator Loss: 0.7121
Epoch 1/2... Discriminator Loss: 1.3866... Generator Loss: 0.7341
Epoch 1/2... Discriminator Loss: 1.3997... Generator Loss: 0.7386
Epoch 1/2... Discriminator Loss: 1.3914... Generator Loss: 0.6951
Epoch 1/2... Discriminator Loss: 1.3923... Generator Loss: 0.6938
Epoch 1/2... Discriminator Loss: 1.3959... Generator Loss: 0.6892
Epoch 1/2... Discriminator Loss: 1.3691... Generator Loss: 0.7301
Epoch 1/2... Discriminator Loss: 1.3832... Generator Loss: 0.7275
Epoch 1/2... Discriminator Loss: 1.3844... Generator Loss: 0.7246
Epoch 1/2... Discriminator Loss: 1.3814... Generator Loss: 0.7008
Epoch 1/2... Discriminator Loss: 1.3879... Generator Loss: 0.7576
Epoch 1/2... Discriminator Loss: 1.4048... Generator Loss: 0.7024
Epoch 1/2... Discriminator Loss: 1.3798... Generator Loss: 0.7009
Epoch 1/2... Discriminator Loss: 1.4036... Generator Loss: 0.6948
Epoch 1/2... Discriminator Loss: 1.3836... Generator Loss: 0.7326
Epoch 2/2... Discriminator Loss: 1.3832... Generator Loss: 0.7381
Epoch 2/2... Discriminator Loss: 1.3754... Generator Loss: 0.7543
Epoch 2/2... Discriminator Loss: 1.3939... Generator Loss: 0.6999
Epoch 2/2... Discriminator Loss: 1.4089... Generator Loss: 0.7253
Epoch 2/2... Discriminator Loss: 1.3936... Generator Loss: 0.7124
Epoch 2/2... Discriminator Loss: 1.3762... Generator Loss: 0.7095
Epoch 2/2... Discriminator Loss: 1.3778... Generator Loss: 0.7297
Epoch 2/2... Discriminator Loss: 1.3936... Generator Loss: 0.6821
Epoch 2/2... Discriminator Loss: 1.3831... Generator Loss: 0.7259
Epoch 2/2... Discriminator Loss: 1.4224... Generator Loss: 0.6995
Epoch 2/2... Discriminator Loss: 1.3927... Generator Loss: 0.7227
Epoch 2/2... Discriminator Loss: 1.3605... Generator Loss: 0.7588
Epoch 2/2... Discriminator Loss: 1.3683... Generator Loss: 0.6858
Epoch 2/2... Discriminator Loss: 1.3995... Generator Loss: 0.6990
Epoch 2/2... Discriminator Loss: 1.3886... Generator Loss: 0.7505
Epoch 2/2... Discriminator Loss: 1.3693... Generator Loss: 0.7375
Epoch 2/2... Discriminator Loss: 1.3767... Generator Loss: 0.7173
Epoch 2/2... Discriminator Loss: 1.3570... Generator Loss: 0.7462
Epoch 2/2... Discriminator Loss: 1.3723... Generator Loss: 0.7476
Epoch 2/2... Discriminator Loss: 1.3761... Generator Loss: 0.7487
Epoch 2/2... Discriminator Loss: 1.4177... Generator Loss: 0.6745
Epoch 2/2... Discriminator Loss: 1.3768... Generator Loss: 0.6908
Epoch 2/2... Discriminator Loss: 1.3630... Generator Loss: 0.7235
Epoch 2/2... Discriminator Loss: 1.4018... Generator Loss: 0.7036
Epoch 2/2... Discriminator Loss: 1.3968... Generator Loss: 0.7231
Epoch 2/2... Discriminator Loss: 1.3768... Generator Loss: 0.7200
Epoch 2/2... Discriminator Loss: 1.3526... Generator Loss: 0.7408
Epoch 2/2... Discriminator Loss: 1.4212... Generator Loss: 0.6745
Epoch 2/2... Discriminator Loss: 1.3888... Generator Loss: 0.6581
Epoch 2/2... Discriminator Loss: 1.3904... Generator Loss: 0.6896
Epoch 2/2... Discriminator Loss: 1.3938... Generator Loss: 0.7117
Epoch 2/2... Discriminator Loss: 1.3679... Generator Loss: 0.6761
Epoch 2/2... Discriminator Loss: 1.3852... Generator Loss: 0.7334
Epoch 2/2... Discriminator Loss: 1.3849... Generator Loss: 0.7308
Epoch 2/2... Discriminator Loss: 1.3740... Generator Loss: 0.6909
Epoch 2/2... Discriminator Loss: 1.3970... Generator Loss: 0.6660
Epoch 2/2... Discriminator Loss: 1.3837... Generator Loss: 0.6969
Epoch 2/2... Discriminator Loss: 1.3949... Generator Loss: 0.7384
Epoch 2/2... Discriminator Loss: 1.4014... Generator Loss: 0.6951
Epoch 2/2... Discriminator Loss: 1.3727... Generator Loss: 0.7237
Epoch 2/2... Discriminator Loss: 1.3926... Generator Loss: 0.6671
Epoch 2/2... Discriminator Loss: 1.3869... Generator Loss: 0.7400
Epoch 2/2... Discriminator Loss: 1.3900... Generator Loss: 0.7144
Epoch 2/2... Discriminator Loss: 1.3739... Generator Loss: 0.6928
Epoch 2/2... Discriminator Loss: 1.3848... Generator Loss: 0.7254
Epoch 2/2... Discriminator Loss: 1.3767... Generator Loss: 0.7292
Epoch 2/2... Discriminator Loss: 1.3647... Generator Loss: 0.7505
Epoch 2/2... Discriminator Loss: 1.3525... Generator Loss: 0.7161
Epoch 2/2... Discriminator Loss: 1.3844... Generator Loss: 0.7084
Epoch 2/2... Discriminator Loss: 1.4027... Generator Loss: 0.6906
Epoch 2/2... Discriminator Loss: 1.3649... Generator Loss: 0.7450
Epoch 2/2... Discriminator Loss: 1.3919... Generator Loss: 0.6756
Epoch 2/2... Discriminator Loss: 1.3758... Generator Loss: 0.7396
Epoch 2/2... Discriminator Loss: 1.3612... Generator Loss: 0.7171
Epoch 2/2... Discriminator Loss: 1.3877... Generator Loss: 0.7305
Epoch 2/2... Discriminator Loss: 1.3798... Generator Loss: 0.6851
Epoch 2/2... Discriminator Loss: 1.3919... Generator Loss: 0.6757
Epoch 2/2... Discriminator Loss: 1.3975... Generator Loss: 0.6790
Epoch 2/2... Discriminator Loss: 1.3727... Generator Loss: 0.7081
Epoch 2/2... Discriminator Loss: 1.3886... Generator Loss: 0.6995
Epoch 2/2... Discriminator Loss: 1.3479... Generator Loss: 0.7067
Epoch 2/2... Discriminator Loss: 1.3878... Generator Loss: 0.7135
Epoch 2/2... Discriminator Loss: 1.3933... Generator Loss: 0.7508
Epoch 2/2... Discriminator Loss: 1.4049... Generator Loss: 0.6770
Epoch 2/2... Discriminator Loss: 1.3504... Generator Loss: 0.7368
Epoch 2/2... Discriminator Loss: 1.3796... Generator Loss: 0.7097
Epoch 2/2... Discriminator Loss: 1.3880... Generator Loss: 0.6820
Epoch 2/2... Discriminator Loss: 1.3924... Generator Loss: 0.7379
Epoch 2/2... Discriminator Loss: 1.3971... Generator Loss: 0.7106
Epoch 2/2... Discriminator Loss: 1.3562... Generator Loss: 0.7220
Epoch 2/2... Discriminator Loss: 1.3575... Generator Loss: 0.7037
Epoch 2/2... Discriminator Loss: 1.3688... Generator Loss: 0.6758
Epoch 2/2... Discriminator Loss: 1.3859... Generator Loss: 0.7065
Epoch 2/2... Discriminator Loss: 1.3668... Generator Loss: 0.6870
Epoch 2/2... Discriminator Loss: 1.4050... Generator Loss: 0.7309
Epoch 2/2... Discriminator Loss: 1.3764... Generator Loss: 0.7066
Epoch 2/2... Discriminator Loss: 1.4115... Generator Loss: 0.6965
Epoch 2/2... Discriminator Loss: 1.3679... Generator Loss: 0.6856
Epoch 2/2... Discriminator Loss: 1.3820... Generator Loss: 0.7185
Epoch 2/2... Discriminator Loss: 1.4011... Generator Loss: 0.6903
Epoch 2/2... Discriminator Loss: 1.3492... Generator Loss: 0.7520
Epoch 2/2... Discriminator Loss: 1.3483... Generator Loss: 0.7066
Epoch 2/2... Discriminator Loss: 1.3890... Generator Loss: 0.7063
Epoch 2/2... Discriminator Loss: 1.3584... Generator Loss: 0.7185
Epoch 2/2... Discriminator Loss: 1.3845... Generator Loss: 0.6886
Epoch 2/2... Discriminator Loss: 1.3671... Generator Loss: 0.6791
Epoch 2/2... Discriminator Loss: 1.3506... Generator Loss: 0.7314
Epoch 2/2... Discriminator Loss: 1.3573... Generator Loss: 0.7013
Epoch 2/2... Discriminator Loss: 1.3868... Generator Loss: 0.7327
Epoch 2/2... Discriminator Loss: 1.3382... Generator Loss: 0.7032
Epoch 2/2... Discriminator Loss: 1.3695... Generator Loss: 0.7343
Epoch 2/2... Discriminator Loss: 1.3701... Generator Loss: 0.6907
Epoch 2/2... Discriminator Loss: 1.3507... Generator Loss: 0.7032
Epoch 2/2... Discriminator Loss: 1.3717... Generator Loss: 0.6977
Epoch 2/2... Discriminator Loss: 1.3863... Generator Loss: 0.7751
Epoch 2/2... Discriminator Loss: 1.3880... Generator Loss: 0.6820
Epoch 2/2... Discriminator Loss: 1.3977... Generator Loss: 0.7156
Epoch 2/2... Discriminator Loss: 1.3652... Generator Loss: 0.7048
Epoch 2/2... Discriminator Loss: 1.3807... Generator Loss: 0.7136
Epoch 2/2... Discriminator Loss: 1.3590... Generator Loss: 0.7065
Epoch 2/2... Discriminator Loss: 1.3994... Generator Loss: 0.7092
Epoch 2/2... Discriminator Loss: 1.3939... Generator Loss: 0.7038
Epoch 2/2... Discriminator Loss: 1.3635... Generator Loss: 0.7171
Epoch 2/2... Discriminator Loss: 1.3900... Generator Loss: 0.6897
Epoch 2/2... Discriminator Loss: 1.3521... Generator Loss: 0.7081
Epoch 2/2... Discriminator Loss: 1.3575... Generator Loss: 0.7186
Epoch 2/2... Discriminator Loss: 1.3700... Generator Loss: 0.6871
Epoch 2/2... Discriminator Loss: 1.3736... Generator Loss: 0.7158
Epoch 2/2... Discriminator Loss: 1.3441... Generator Loss: 0.7313
Epoch 2/2... Discriminator Loss: 1.3855... Generator Loss: 0.7391
Epoch 2/2... Discriminator Loss: 1.3810... Generator Loss: 0.6987
Epoch 2/2... Discriminator Loss: 1.3668... Generator Loss: 0.6895
Epoch 2/2... Discriminator Loss: 1.3654... Generator Loss: 0.7330
Epoch 2/2... Discriminator Loss: 1.3937... Generator Loss: 0.7073
Epoch 2/2... Discriminator Loss: 1.3516... Generator Loss: 0.7253
Epoch 2/2... Discriminator Loss: 1.3380... Generator Loss: 0.7524
Epoch 2/2... Discriminator Loss: 1.3713... Generator Loss: 0.7144
Epoch 2/2... Discriminator Loss: 1.3707... Generator Loss: 0.6869
Epoch 2/2... Discriminator Loss: 1.3777... Generator Loss: 0.7027
Epoch 2/2... Discriminator Loss: 1.3766... Generator Loss: 0.7044
Epoch 2/2... Discriminator Loss: 1.3573... Generator Loss: 0.7184
Epoch 2/2... Discriminator Loss: 1.3804... Generator Loss: 0.7075
Epoch 2/2... Discriminator Loss: 1.3617... Generator Loss: 0.7159
Epoch 2/2... Discriminator Loss: 1.3904... Generator Loss: 0.7093
Epoch 2/2... Discriminator Loss: 1.3757... Generator Loss: 0.6803
Epoch 2/2... Discriminator Loss: 1.3627... Generator Loss: 0.7177
Epoch 2/2... Discriminator Loss: 1.3587... Generator Loss: 0.7439
Epoch 2/2... Discriminator Loss: 1.3798... Generator Loss: 0.6893
Epoch 2/2... Discriminator Loss: 1.3771... Generator Loss: 0.7309
Epoch 2/2... Discriminator Loss: 1.3584... Generator Loss: 0.7519
Epoch 2/2... Discriminator Loss: 1.3700... Generator Loss: 0.7051
Epoch 2/2... Discriminator Loss: 1.4208... Generator Loss: 0.6545
Epoch 2/2... Discriminator Loss: 1.3810... Generator Loss: 0.7368
Epoch 2/2... Discriminator Loss: 1.3901... Generator Loss: 0.7244
Epoch 2/2... Discriminator Loss: 1.4027... Generator Loss: 0.7032
Epoch 2/2... Discriminator Loss: 1.3455... Generator Loss: 0.7100
Epoch 2/2... Discriminator Loss: 1.3259... Generator Loss: 0.7571
Epoch 2/2... Discriminator Loss: 1.3676... Generator Loss: 0.6869
Epoch 2/2... Discriminator Loss: 1.3768... Generator Loss: 0.6958
Epoch 2/2... Discriminator Loss: 1.3778... Generator Loss: 0.7700
Epoch 2/2... Discriminator Loss: 1.3922... Generator Loss: 0.7031
Epoch 2/2... Discriminator Loss: 1.3807... Generator Loss: 0.6527
Epoch 2/2... Discriminator Loss: 1.3406... Generator Loss: 0.6830
Epoch 2/2... Discriminator Loss: 1.3504... Generator Loss: 0.7631
Epoch 2/2... Discriminator Loss: 1.3634... Generator Loss: 0.7185
Epoch 2/2... Discriminator Loss: 1.3793... Generator Loss: 0.7436
Epoch 2/2... Discriminator Loss: 1.3579... Generator Loss: 0.7310
Epoch 2/2... Discriminator Loss: 1.3652... Generator Loss: 0.6796
Epoch 2/2... Discriminator Loss: 1.3619... Generator Loss: 0.7122
Epoch 2/2... Discriminator Loss: 1.3256... Generator Loss: 0.7206
Epoch 2/2... Discriminator Loss: 1.3715... Generator Loss: 0.7011
Epoch 2/2... Discriminator Loss: 1.3488... Generator Loss: 0.7628
Epoch 2/2... Discriminator Loss: 1.3849... Generator Loss: 0.6825
Epoch 2/2... Discriminator Loss: 1.3698... Generator Loss: 0.7133
Epoch 2/2... Discriminator Loss: 1.4101... Generator Loss: 0.7025
Epoch 2/2... Discriminator Loss: 1.4043... Generator Loss: 0.7024
Epoch 2/2... Discriminator Loss: 1.3494... Generator Loss: 0.7335
Epoch 2/2... Discriminator Loss: 1.3800... Generator Loss: 0.7109
Epoch 2/2... Discriminator Loss: 1.3952... Generator Loss: 0.6811
Epoch 2/2... Discriminator Loss: 1.3702... Generator Loss: 0.7187
Epoch 2/2... Discriminator Loss: 1.3734... Generator Loss: 0.6887
Epoch 2/2... Discriminator Loss: 1.3773... Generator Loss: 0.7097
Epoch 2/2... Discriminator Loss: 1.3411... Generator Loss: 0.7158
Epoch 2/2... Discriminator Loss: 1.3226... Generator Loss: 0.7419
Epoch 2/2... Discriminator Loss: 1.3732... Generator Loss: 0.7504
Epoch 2/2... Discriminator Loss: 1.3625... Generator Loss: 0.7280
Epoch 2/2... Discriminator Loss: 1.3669... Generator Loss: 0.7082
Epoch 2/2... Discriminator Loss: 1.3680... Generator Loss: 0.6759
Epoch 2/2... Discriminator Loss: 1.3521... Generator Loss: 0.7777
Epoch 2/2... Discriminator Loss: 1.3451... Generator Loss: 0.6950
Epoch 2/2... Discriminator Loss: 1.4073... Generator Loss: 0.7177
Epoch 2/2... Discriminator Loss: 1.3242... Generator Loss: 0.6488
Epoch 2/2... Discriminator Loss: 1.4136... Generator Loss: 0.6534
Epoch 2/2... Discriminator Loss: 1.3164... Generator Loss: 0.7496
Epoch 2/2... Discriminator Loss: 1.3473... Generator Loss: 0.7401
Epoch 2/2... Discriminator Loss: 1.3641... Generator Loss: 0.7259
Epoch 2/2... Discriminator Loss: 1.3767... Generator Loss: 0.7032
Epoch 2/2... Discriminator Loss: 1.3723... Generator Loss: 0.7173
Epoch 2/2... Discriminator Loss: 1.3967... Generator Loss: 0.7185
Epoch 2/2... Discriminator Loss: 1.3638... Generator Loss: 0.6925
Epoch 2/2... Discriminator Loss: 1.3699... Generator Loss: 0.7081
Epoch 2/2... Discriminator Loss: 1.3619... Generator Loss: 0.6924
Epoch 2/2... Discriminator Loss: 1.3849... Generator Loss: 0.6940
Epoch 2/2... Discriminator Loss: 1.3830... Generator Loss: 0.7128
Epoch 2/2... Discriminator Loss: 1.3394... Generator Loss: 0.7371
Epoch 2/2... Discriminator Loss: 1.3617... Generator Loss: 0.7319
Epoch 2/2... Discriminator Loss: 1.3634... Generator Loss: 0.7005
Epoch 2/2... Discriminator Loss: 1.3440... Generator Loss: 0.7085

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [14]:
batch_size = 16
z_dim = 128
learning_rate = 0.0002
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/1... Discriminator Loss: 1.6846... Generator Loss: 0.7843
Epoch 1/1... Discriminator Loss: 1.0965... Generator Loss: 1.8101
Epoch 1/1... Discriminator Loss: 0.9533... Generator Loss: 1.4082
Epoch 1/1... Discriminator Loss: 0.4560... Generator Loss: 2.4948
Epoch 1/1... Discriminator Loss: 1.1085... Generator Loss: 1.1454
Epoch 1/1... Discriminator Loss: 0.6607... Generator Loss: 1.9875
Epoch 1/1... Discriminator Loss: 0.5197... Generator Loss: 1.6256
Epoch 1/1... Discriminator Loss: 0.6677... Generator Loss: 1.4409
Epoch 1/1... Discriminator Loss: 0.5187... Generator Loss: 2.0874
Epoch 1/1... Discriminator Loss: 0.3417... Generator Loss: 2.6751
Epoch 1/1... Discriminator Loss: 0.4268... Generator Loss: 2.5341
Epoch 1/1... Discriminator Loss: 0.4790... Generator Loss: 1.7284
Epoch 1/1... Discriminator Loss: 0.5349... Generator Loss: 2.0630
Epoch 1/1... Discriminator Loss: 0.9731... Generator Loss: 1.3143
Epoch 1/1... Discriminator Loss: 0.7852... Generator Loss: 1.5314
Epoch 1/1... Discriminator Loss: 0.9585... Generator Loss: 1.3441
Epoch 1/1... Discriminator Loss: 0.7649... Generator Loss: 1.3039
Epoch 1/1... Discriminator Loss: 0.7638... Generator Loss: 1.4068
Epoch 1/1... Discriminator Loss: 0.7087... Generator Loss: 1.3235
Epoch 1/1... Discriminator Loss: 0.7530... Generator Loss: 1.2114
Epoch 1/1... Discriminator Loss: 0.8833... Generator Loss: 1.1836
Epoch 1/1... Discriminator Loss: 1.1548... Generator Loss: 1.3186
Epoch 1/1... Discriminator Loss: 1.0946... Generator Loss: 0.8978
Epoch 1/1... Discriminator Loss: 0.7972... Generator Loss: 1.2197
Epoch 1/1... Discriminator Loss: 1.1590... Generator Loss: 0.7820
Epoch 1/1... Discriminator Loss: 0.8669... Generator Loss: 1.2107
Epoch 1/1... Discriminator Loss: 0.8529... Generator Loss: 1.1792
Epoch 1/1... Discriminator Loss: 1.0583... Generator Loss: 0.9691
Epoch 1/1... Discriminator Loss: 1.1488... Generator Loss: 0.9467
Epoch 1/1... Discriminator Loss: 1.1230... Generator Loss: 0.8070
Epoch 1/1... Discriminator Loss: 1.2393... Generator Loss: 0.9035
Epoch 1/1... Discriminator Loss: 1.1123... Generator Loss: 0.8992
Epoch 1/1... Discriminator Loss: 1.1326... Generator Loss: 0.9725
Epoch 1/1... Discriminator Loss: 1.2948... Generator Loss: 0.8177
Epoch 1/1... Discriminator Loss: 1.0950... Generator Loss: 0.9891
Epoch 1/1... Discriminator Loss: 1.1522... Generator Loss: 0.9106
Epoch 1/1... Discriminator Loss: 1.1431... Generator Loss: 0.8096
Epoch 1/1... Discriminator Loss: 1.0926... Generator Loss: 0.9108
Epoch 1/1... Discriminator Loss: 1.2138... Generator Loss: 0.7984
Epoch 1/1... Discriminator Loss: 1.0897... Generator Loss: 0.9834
Epoch 1/1... Discriminator Loss: 1.1739... Generator Loss: 0.8121
Epoch 1/1... Discriminator Loss: 1.2046... Generator Loss: 1.0450
Epoch 1/1... Discriminator Loss: 1.0869... Generator Loss: 0.9028
Epoch 1/1... Discriminator Loss: 1.2698... Generator Loss: 0.8188
Epoch 1/1... Discriminator Loss: 0.9067... Generator Loss: 1.0129
Epoch 1/1... Discriminator Loss: 1.0524... Generator Loss: 1.0028
Epoch 1/1... Discriminator Loss: 1.0705... Generator Loss: 0.9190
Epoch 1/1... Discriminator Loss: 1.0355... Generator Loss: 1.0140
Epoch 1/1... Discriminator Loss: 1.3372... Generator Loss: 0.8024
Epoch 1/1... Discriminator Loss: 1.1506... Generator Loss: 0.8505
Epoch 1/1... Discriminator Loss: 1.2575... Generator Loss: 0.8547
Epoch 1/1... Discriminator Loss: 1.0085... Generator Loss: 0.8944
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.8484
Epoch 1/1... Discriminator Loss: 1.1082... Generator Loss: 0.9847
Epoch 1/1... Discriminator Loss: 1.1177... Generator Loss: 0.8967
Epoch 1/1... Discriminator Loss: 1.0963... Generator Loss: 0.9019
Epoch 1/1... Discriminator Loss: 1.1065... Generator Loss: 0.8902
Epoch 1/1... Discriminator Loss: 1.2735... Generator Loss: 0.8522
Epoch 1/1... Discriminator Loss: 1.2533... Generator Loss: 0.8778
Epoch 1/1... Discriminator Loss: 1.4131... Generator Loss: 0.8028
Epoch 1/1... Discriminator Loss: 1.2722... Generator Loss: 0.7575
Epoch 1/1... Discriminator Loss: 1.3169... Generator Loss: 0.7811
Epoch 1/1... Discriminator Loss: 1.2882... Generator Loss: 0.7651
Epoch 1/1... Discriminator Loss: 1.2346... Generator Loss: 0.8077
Epoch 1/1... Discriminator Loss: 1.3303... Generator Loss: 0.7836
Epoch 1/1... Discriminator Loss: 1.3564... Generator Loss: 0.8642
Epoch 1/1... Discriminator Loss: 1.2512... Generator Loss: 0.8337
Epoch 1/1... Discriminator Loss: 1.3889... Generator Loss: 0.6788
Epoch 1/1... Discriminator Loss: 1.2760... Generator Loss: 0.8021
Epoch 1/1... Discriminator Loss: 1.2365... Generator Loss: 0.7888
Epoch 1/1... Discriminator Loss: 1.3537... Generator Loss: 0.6765
Epoch 1/1... Discriminator Loss: 1.3264... Generator Loss: 0.7453
Epoch 1/1... Discriminator Loss: 1.3249... Generator Loss: 0.8216
Epoch 1/1... Discriminator Loss: 1.3860... Generator Loss: 0.6852
Epoch 1/1... Discriminator Loss: 1.4221... Generator Loss: 0.7135
Epoch 1/1... Discriminator Loss: 1.4757... Generator Loss: 0.7597
Epoch 1/1... Discriminator Loss: 1.3822... Generator Loss: 0.7663
Epoch 1/1... Discriminator Loss: 1.3195... Generator Loss: 0.7555
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7487
Epoch 1/1... Discriminator Loss: 1.4236... Generator Loss: 0.8465
Epoch 1/1... Discriminator Loss: 1.4396... Generator Loss: 0.6831
Epoch 1/1... Discriminator Loss: 1.2885... Generator Loss: 0.8041
Epoch 1/1... Discriminator Loss: 1.3503... Generator Loss: 0.7701
Epoch 1/1... Discriminator Loss: 1.4262... Generator Loss: 0.7847
Epoch 1/1... Discriminator Loss: 1.4416... Generator Loss: 0.7382
Epoch 1/1... Discriminator Loss: 1.4701... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.4499... Generator Loss: 0.7846
Epoch 1/1... Discriminator Loss: 1.4601... Generator Loss: 0.6786
Epoch 1/1... Discriminator Loss: 1.4033... Generator Loss: 0.8281
Epoch 1/1... Discriminator Loss: 1.4335... Generator Loss: 0.6439
Epoch 1/1... Discriminator Loss: 1.3411... Generator Loss: 0.7709
Epoch 1/1... Discriminator Loss: 1.4361... Generator Loss: 0.6899
Epoch 1/1... Discriminator Loss: 1.3915... Generator Loss: 0.7899
Epoch 1/1... Discriminator Loss: 1.3624... Generator Loss: 0.7974
Epoch 1/1... Discriminator Loss: 1.3397... Generator Loss: 0.6986
Epoch 1/1... Discriminator Loss: 1.3963... Generator Loss: 0.8068
Epoch 1/1... Discriminator Loss: 1.4484... Generator Loss: 0.6158
Epoch 1/1... Discriminator Loss: 1.4662... Generator Loss: 0.7191
Epoch 1/1... Discriminator Loss: 1.4377... Generator Loss: 0.7517
Epoch 1/1... Discriminator Loss: 1.3944... Generator Loss: 0.7885
Epoch 1/1... Discriminator Loss: 1.3938... Generator Loss: 0.7899
Epoch 1/1... Discriminator Loss: 1.4184... Generator Loss: 0.7235
Epoch 1/1... Discriminator Loss: 1.4357... Generator Loss: 0.7508
Epoch 1/1... Discriminator Loss: 1.3989... Generator Loss: 0.7225
Epoch 1/1... Discriminator Loss: 1.4416... Generator Loss: 0.6909
Epoch 1/1... Discriminator Loss: 1.4662... Generator Loss: 0.7552
Epoch 1/1... Discriminator Loss: 1.4052... Generator Loss: 0.8212
Epoch 1/1... Discriminator Loss: 1.4441... Generator Loss: 0.7321
Epoch 1/1... Discriminator Loss: 1.4164... Generator Loss: 0.7121
Epoch 1/1... Discriminator Loss: 1.4544... Generator Loss: 0.6984
Epoch 1/1... Discriminator Loss: 1.4457... Generator Loss: 0.6520
Epoch 1/1... Discriminator Loss: 1.4815... Generator Loss: 0.7382
Epoch 1/1... Discriminator Loss: 1.4754... Generator Loss: 0.7350
Epoch 1/1... Discriminator Loss: 1.5134... Generator Loss: 0.6508
Epoch 1/1... Discriminator Loss: 1.4076... Generator Loss: 0.7028
Epoch 1/1... Discriminator Loss: 1.4176... Generator Loss: 0.6332
Epoch 1/1... Discriminator Loss: 1.4349... Generator Loss: 0.7490
Epoch 1/1... Discriminator Loss: 1.5490... Generator Loss: 0.7615
Epoch 1/1... Discriminator Loss: 1.4238... Generator Loss: 0.6761
Epoch 1/1... Discriminator Loss: 1.3751... Generator Loss: 0.8049
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.8000
Epoch 1/1... Discriminator Loss: 1.4300... Generator Loss: 0.6913
Epoch 1/1... Discriminator Loss: 1.4187... Generator Loss: 0.7314
Epoch 1/1... Discriminator Loss: 1.3660... Generator Loss: 0.7826
Epoch 1/1... Discriminator Loss: 1.3961... Generator Loss: 0.8335
Epoch 1/1... Discriminator Loss: 1.4287... Generator Loss: 0.7150
Epoch 1/1... Discriminator Loss: 1.4060... Generator Loss: 0.7011
Epoch 1/1... Discriminator Loss: 1.4394... Generator Loss: 0.7208
Epoch 1/1... Discriminator Loss: 1.3980... Generator Loss: 0.6756
Epoch 1/1... Discriminator Loss: 1.3642... Generator Loss: 0.7649
Epoch 1/1... Discriminator Loss: 1.4794... Generator Loss: 0.6778
Epoch 1/1... Discriminator Loss: 1.3842... Generator Loss: 0.6835
Epoch 1/1... Discriminator Loss: 1.3733... Generator Loss: 0.6895
Epoch 1/1... Discriminator Loss: 1.3658... Generator Loss: 0.6792
Epoch 1/1... Discriminator Loss: 1.3736... Generator Loss: 0.7139
Epoch 1/1... Discriminator Loss: 1.4081... Generator Loss: 0.7202
Epoch 1/1... Discriminator Loss: 1.4269... Generator Loss: 0.7075
Epoch 1/1... Discriminator Loss: 1.4657... Generator Loss: 0.6722
Epoch 1/1... Discriminator Loss: 1.4022... Generator Loss: 0.6659
Epoch 1/1... Discriminator Loss: 1.4096... Generator Loss: 0.7122
Epoch 1/1... Discriminator Loss: 1.3936... Generator Loss: 0.6973
Epoch 1/1... Discriminator Loss: 1.3690... Generator Loss: 0.6755
Epoch 1/1... Discriminator Loss: 1.4454... Generator Loss: 0.6631
Epoch 1/1... Discriminator Loss: 1.3639... Generator Loss: 0.7491
Epoch 1/1... Discriminator Loss: 1.4188... Generator Loss: 0.7599
Epoch 1/1... Discriminator Loss: 1.4061... Generator Loss: 0.8132
Epoch 1/1... Discriminator Loss: 1.4477... Generator Loss: 0.7651
Epoch 1/1... Discriminator Loss: 1.4131... Generator Loss: 0.7535
Epoch 1/1... Discriminator Loss: 1.4705... Generator Loss: 0.7217
Epoch 1/1... Discriminator Loss: 1.4345... Generator Loss: 0.7371
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.6481
Epoch 1/1... Discriminator Loss: 1.3825... Generator Loss: 0.7842
Epoch 1/1... Discriminator Loss: 1.4064... Generator Loss: 0.7315
Epoch 1/1... Discriminator Loss: 1.4550... Generator Loss: 0.6473
Epoch 1/1... Discriminator Loss: 1.4557... Generator Loss: 0.6319
Epoch 1/1... Discriminator Loss: 1.3241... Generator Loss: 0.7284
Epoch 1/1... Discriminator Loss: 1.4448... Generator Loss: 0.6721
Epoch 1/1... Discriminator Loss: 1.3714... Generator Loss: 0.7615
Epoch 1/1... Discriminator Loss: 1.3945... Generator Loss: 0.7696
Epoch 1/1... Discriminator Loss: 1.4063... Generator Loss: 0.7201
Epoch 1/1... Discriminator Loss: 1.4205... Generator Loss: 0.6563
Epoch 1/1... Discriminator Loss: 1.3799... Generator Loss: 0.6890
Epoch 1/1... Discriminator Loss: 1.4211... Generator Loss: 0.6861
Epoch 1/1... Discriminator Loss: 1.3874... Generator Loss: 0.7244
Epoch 1/1... Discriminator Loss: 1.4265... Generator Loss: 0.7561
Epoch 1/1... Discriminator Loss: 1.4352... Generator Loss: 0.7946
Epoch 1/1... Discriminator Loss: 1.3762... Generator Loss: 0.7441
Epoch 1/1... Discriminator Loss: 1.4284... Generator Loss: 0.7622
Epoch 1/1... Discriminator Loss: 1.4584... Generator Loss: 0.7035
Epoch 1/1... Discriminator Loss: 1.3886... Generator Loss: 0.8089
Epoch 1/1... Discriminator Loss: 1.4167... Generator Loss: 0.6591
Epoch 1/1... Discriminator Loss: 1.4522... Generator Loss: 0.7205
Epoch 1/1... Discriminator Loss: 1.3616... Generator Loss: 0.7395
Epoch 1/1... Discriminator Loss: 1.4489... Generator Loss: 0.7093
Epoch 1/1... Discriminator Loss: 1.3961... Generator Loss: 0.7072
Epoch 1/1... Discriminator Loss: 1.3953... Generator Loss: 0.7241
Epoch 1/1... Discriminator Loss: 1.3832... Generator Loss: 0.7162
Epoch 1/1... Discriminator Loss: 1.4200... Generator Loss: 0.7288
Epoch 1/1... Discriminator Loss: 1.4037... Generator Loss: 0.6762
Epoch 1/1... Discriminator Loss: 1.4274... Generator Loss: 0.6737
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7855
Epoch 1/1... Discriminator Loss: 1.4070... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.7282
Epoch 1/1... Discriminator Loss: 1.4108... Generator Loss: 0.7804
Epoch 1/1... Discriminator Loss: 1.4279... Generator Loss: 0.6866
Epoch 1/1... Discriminator Loss: 1.4560... Generator Loss: 0.7254
Epoch 1/1... Discriminator Loss: 1.4423... Generator Loss: 0.6803
Epoch 1/1... Discriminator Loss: 1.3877... Generator Loss: 0.8383
Epoch 1/1... Discriminator Loss: 1.3830... Generator Loss: 0.8148
Epoch 1/1... Discriminator Loss: 1.3733... Generator Loss: 0.7425
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.6928
Epoch 1/1... Discriminator Loss: 1.3602... Generator Loss: 0.7077
Epoch 1/1... Discriminator Loss: 1.4103... Generator Loss: 0.6347
Epoch 1/1... Discriminator Loss: 1.3828... Generator Loss: 0.6975
Epoch 1/1... Discriminator Loss: 1.4269... Generator Loss: 0.7433
Epoch 1/1... Discriminator Loss: 1.4219... Generator Loss: 0.7090
Epoch 1/1... Discriminator Loss: 1.4039... Generator Loss: 0.8041
Epoch 1/1... Discriminator Loss: 1.4103... Generator Loss: 0.7214
Epoch 1/1... Discriminator Loss: 1.4449... Generator Loss: 0.7880
Epoch 1/1... Discriminator Loss: 1.3797... Generator Loss: 0.7790
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.7562
Epoch 1/1... Discriminator Loss: 1.3915... Generator Loss: 0.7150
Epoch 1/1... Discriminator Loss: 1.4113... Generator Loss: 0.6868
Epoch 1/1... Discriminator Loss: 1.4220... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.4430... Generator Loss: 0.6837
Epoch 1/1... Discriminator Loss: 1.4017... Generator Loss: 0.7390
Epoch 1/1... Discriminator Loss: 1.4406... Generator Loss: 0.6873
Epoch 1/1... Discriminator Loss: 1.3942... Generator Loss: 0.7050
Epoch 1/1... Discriminator Loss: 1.4127... Generator Loss: 0.6886
Epoch 1/1... Discriminator Loss: 1.4352... Generator Loss: 0.7061
Epoch 1/1... Discriminator Loss: 1.4049... Generator Loss: 0.7260
Epoch 1/1... Discriminator Loss: 1.4005... Generator Loss: 0.6899
Epoch 1/1... Discriminator Loss: 1.4063... Generator Loss: 0.6932
Epoch 1/1... Discriminator Loss: 1.4348... Generator Loss: 0.6627
Epoch 1/1... Discriminator Loss: 1.4084... Generator Loss: 0.6780
Epoch 1/1... Discriminator Loss: 1.4144... Generator Loss: 0.6776
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.6849
Epoch 1/1... Discriminator Loss: 1.3638... Generator Loss: 0.7602
Epoch 1/1... Discriminator Loss: 1.4083... Generator Loss: 0.6669
Epoch 1/1... Discriminator Loss: 1.4159... Generator Loss: 0.6777
Epoch 1/1... Discriminator Loss: 1.4140... Generator Loss: 0.7385
Epoch 1/1... Discriminator Loss: 1.4020... Generator Loss: 0.6605
Epoch 1/1... Discriminator Loss: 1.3863... Generator Loss: 0.7297
Epoch 1/1... Discriminator Loss: 1.4389... Generator Loss: 0.6880
Epoch 1/1... Discriminator Loss: 1.4108... Generator Loss: 0.7195
Epoch 1/1... Discriminator Loss: 1.3881... Generator Loss: 0.7339
Epoch 1/1... Discriminator Loss: 1.4028... Generator Loss: 0.7449
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.7019
Epoch 1/1... Discriminator Loss: 1.4406... Generator Loss: 0.6574
Epoch 1/1... Discriminator Loss: 1.3985... Generator Loss: 0.6902
Epoch 1/1... Discriminator Loss: 1.3861... Generator Loss: 0.7603
Epoch 1/1... Discriminator Loss: 1.3729... Generator Loss: 0.7644
Epoch 1/1... Discriminator Loss: 1.4044... Generator Loss: 0.6794
Epoch 1/1... Discriminator Loss: 1.4162... Generator Loss: 0.7446
Epoch 1/1... Discriminator Loss: 1.4189... Generator Loss: 0.7662
Epoch 1/1... Discriminator Loss: 1.3803... Generator Loss: 0.7317
Epoch 1/1... Discriminator Loss: 1.4179... Generator Loss: 0.6994
Epoch 1/1... Discriminator Loss: 1.3791... Generator Loss: 0.7298
Epoch 1/1... Discriminator Loss: 1.3746... Generator Loss: 0.7087
Epoch 1/1... Discriminator Loss: 1.3743... Generator Loss: 0.7218
Epoch 1/1... Discriminator Loss: 1.3756... Generator Loss: 0.6773
Epoch 1/1... Discriminator Loss: 1.3940... Generator Loss: 0.7269
Epoch 1/1... Discriminator Loss: 1.4194... Generator Loss: 0.6942
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6557
Epoch 1/1... Discriminator Loss: 1.3729... Generator Loss: 0.7014
Epoch 1/1... Discriminator Loss: 1.3728... Generator Loss: 0.6894
Epoch 1/1... Discriminator Loss: 1.3999... Generator Loss: 0.7238
Epoch 1/1... Discriminator Loss: 1.3619... Generator Loss: 0.7106
Epoch 1/1... Discriminator Loss: 1.4130... Generator Loss: 0.7043
Epoch 1/1... Discriminator Loss: 1.3817... Generator Loss: 0.7555
Epoch 1/1... Discriminator Loss: 1.4209... Generator Loss: 0.7462
Epoch 1/1... Discriminator Loss: 1.4198... Generator Loss: 0.7090
Epoch 1/1... Discriminator Loss: 1.3714... Generator Loss: 0.7007
Epoch 1/1... Discriminator Loss: 1.3980... Generator Loss: 0.7335
Epoch 1/1... Discriminator Loss: 1.3789... Generator Loss: 0.7350
Epoch 1/1... Discriminator Loss: 1.3731... Generator Loss: 0.7052
Epoch 1/1... Discriminator Loss: 1.3809... Generator Loss: 0.7029
Epoch 1/1... Discriminator Loss: 1.4112... Generator Loss: 0.6825
Epoch 1/1... Discriminator Loss: 1.4161... Generator Loss: 0.6840
Epoch 1/1... Discriminator Loss: 1.3909... Generator Loss: 0.6599
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7200
Epoch 1/1... Discriminator Loss: 1.4093... Generator Loss: 0.7385
Epoch 1/1... Discriminator Loss: 1.4019... Generator Loss: 0.7319
Epoch 1/1... Discriminator Loss: 1.3909... Generator Loss: 0.7187
Epoch 1/1... Discriminator Loss: 1.3727... Generator Loss: 0.6821
Epoch 1/1... Discriminator Loss: 1.3969... Generator Loss: 0.7276
Epoch 1/1... Discriminator Loss: 1.3602... Generator Loss: 0.7254
Epoch 1/1... Discriminator Loss: 1.4158... Generator Loss: 0.7529
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.6860
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.7101
Epoch 1/1... Discriminator Loss: 1.3991... Generator Loss: 0.6770
Epoch 1/1... Discriminator Loss: 1.3891... Generator Loss: 0.7383
Epoch 1/1... Discriminator Loss: 1.3988... Generator Loss: 0.7507
Epoch 1/1... Discriminator Loss: 1.4109... Generator Loss: 0.7015
Epoch 1/1... Discriminator Loss: 1.3943... Generator Loss: 0.6582
Epoch 1/1... Discriminator Loss: 1.4057... Generator Loss: 0.6990
Epoch 1/1... Discriminator Loss: 1.3670... Generator Loss: 0.6981
Epoch 1/1... Discriminator Loss: 1.4357... Generator Loss: 0.6939
Epoch 1/1... Discriminator Loss: 1.3967... Generator Loss: 0.6621
Epoch 1/1... Discriminator Loss: 1.3978... Generator Loss: 0.7277
Epoch 1/1... Discriminator Loss: 1.4063... Generator Loss: 0.7203
Epoch 1/1... Discriminator Loss: 1.3892... Generator Loss: 0.7071
Epoch 1/1... Discriminator Loss: 1.3886... Generator Loss: 0.7647
Epoch 1/1... Discriminator Loss: 1.3965... Generator Loss: 0.6406
Epoch 1/1... Discriminator Loss: 1.4195... Generator Loss: 0.6811
Epoch 1/1... Discriminator Loss: 1.4076... Generator Loss: 0.6930
Epoch 1/1... Discriminator Loss: 1.3577... Generator Loss: 0.7503
Epoch 1/1... Discriminator Loss: 1.3716... Generator Loss: 0.7164
Epoch 1/1... Discriminator Loss: 1.3678... Generator Loss: 0.7351
Epoch 1/1... Discriminator Loss: 1.3620... Generator Loss: 0.7562
Epoch 1/1... Discriminator Loss: 1.3878... Generator Loss: 0.7845
Epoch 1/1... Discriminator Loss: 1.3977... Generator Loss: 0.6584
Epoch 1/1... Discriminator Loss: 1.3937... Generator Loss: 0.6893
Epoch 1/1... Discriminator Loss: 1.4070... Generator Loss: 0.6489
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.6906
Epoch 1/1... Discriminator Loss: 1.3894... Generator Loss: 0.7234
Epoch 1/1... Discriminator Loss: 1.4035... Generator Loss: 0.6729
Epoch 1/1... Discriminator Loss: 1.3779... Generator Loss: 0.6729
Epoch 1/1... Discriminator Loss: 1.4137... Generator Loss: 0.6805
Epoch 1/1... Discriminator Loss: 1.3773... Generator Loss: 0.6797
Epoch 1/1... Discriminator Loss: 1.3763... Generator Loss: 0.7419
Epoch 1/1... Discriminator Loss: 1.3759... Generator Loss: 0.7134
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7403
Epoch 1/1... Discriminator Loss: 1.3873... Generator Loss: 0.7136
Epoch 1/1... Discriminator Loss: 1.4091... Generator Loss: 0.7374
Epoch 1/1... Discriminator Loss: 1.3826... Generator Loss: 0.6705
Epoch 1/1... Discriminator Loss: 1.3970... Generator Loss: 0.6874
Epoch 1/1... Discriminator Loss: 1.3710... Generator Loss: 0.7165
Epoch 1/1... Discriminator Loss: 1.4107... Generator Loss: 0.6941
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.6794
Epoch 1/1... Discriminator Loss: 1.3624... Generator Loss: 0.6823
Epoch 1/1... Discriminator Loss: 1.4038... Generator Loss: 0.7354
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.7199
Epoch 1/1... Discriminator Loss: 1.3718... Generator Loss: 0.7294
Epoch 1/1... Discriminator Loss: 1.4101... Generator Loss: 0.6856
Epoch 1/1... Discriminator Loss: 1.3920... Generator Loss: 0.7542
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.6943
Epoch 1/1... Discriminator Loss: 1.4068... Generator Loss: 0.7147
Epoch 1/1... Discriminator Loss: 1.4055... Generator Loss: 0.6898
Epoch 1/1... Discriminator Loss: 1.3826... Generator Loss: 0.7181
Epoch 1/1... Discriminator Loss: 1.3977... Generator Loss: 0.6849
Epoch 1/1... Discriminator Loss: 1.4090... Generator Loss: 0.7009
Epoch 1/1... Discriminator Loss: 1.3714... Generator Loss: 0.7096
Epoch 1/1... Discriminator Loss: 1.4138... Generator Loss: 0.6808
Epoch 1/1... Discriminator Loss: 1.4137... Generator Loss: 0.7031
Epoch 1/1... Discriminator Loss: 1.3541... Generator Loss: 0.6986
Epoch 1/1... Discriminator Loss: 1.3966... Generator Loss: 0.6778
Epoch 1/1... Discriminator Loss: 1.3912... Generator Loss: 0.7295
Epoch 1/1... Discriminator Loss: 1.3639... Generator Loss: 0.6786
Epoch 1/1... Discriminator Loss: 1.4049... Generator Loss: 0.6971
Epoch 1/1... Discriminator Loss: 1.4026... Generator Loss: 0.6772
Epoch 1/1... Discriminator Loss: 1.4045... Generator Loss: 0.7459
Epoch 1/1... Discriminator Loss: 1.3690... Generator Loss: 0.6624
Epoch 1/1... Discriminator Loss: 1.3664... Generator Loss: 0.7289
Epoch 1/1... Discriminator Loss: 1.3580... Generator Loss: 0.6623
Epoch 1/1... Discriminator Loss: 1.3568... Generator Loss: 0.7138
Epoch 1/1... Discriminator Loss: 1.3836... Generator Loss: 0.6825
Epoch 1/1... Discriminator Loss: 1.3995... Generator Loss: 0.7021
Epoch 1/1... Discriminator Loss: 1.3839... Generator Loss: 0.7036
Epoch 1/1... Discriminator Loss: 1.3934... Generator Loss: 0.6845
Epoch 1/1... Discriminator Loss: 1.3719... Generator Loss: 0.7188
Epoch 1/1... Discriminator Loss: 1.4119... Generator Loss: 0.7394
Epoch 1/1... Discriminator Loss: 1.3912... Generator Loss: 0.6931
Epoch 1/1... Discriminator Loss: 1.3842... Generator Loss: 0.6809
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.7204
Epoch 1/1... Discriminator Loss: 1.4002... Generator Loss: 0.6551
Epoch 1/1... Discriminator Loss: 1.3766... Generator Loss: 0.6999
Epoch 1/1... Discriminator Loss: 1.4173... Generator Loss: 0.6925
Epoch 1/1... Discriminator Loss: 1.4073... Generator Loss: 0.6639
Epoch 1/1... Discriminator Loss: 1.4092... Generator Loss: 0.7216
Epoch 1/1... Discriminator Loss: 1.4010... Generator Loss: 0.6851
Epoch 1/1... Discriminator Loss: 1.3878... Generator Loss: 0.6911
Epoch 1/1... Discriminator Loss: 1.4047... Generator Loss: 0.6867
Epoch 1/1... Discriminator Loss: 1.3806... Generator Loss: 0.6790
Epoch 1/1... Discriminator Loss: 1.4142... Generator Loss: 0.7232
Epoch 1/1... Discriminator Loss: 1.3632... Generator Loss: 0.6927
Epoch 1/1... Discriminator Loss: 1.3709... Generator Loss: 0.7164
Epoch 1/1... Discriminator Loss: 1.3856... Generator Loss: 0.6804
Epoch 1/1... Discriminator Loss: 1.3992... Generator Loss: 0.7319
Epoch 1/1... Discriminator Loss: 1.4198... Generator Loss: 0.6724
Epoch 1/1... Discriminator Loss: 1.3951... Generator Loss: 0.6616
Epoch 1/1... Discriminator Loss: 1.4266... Generator Loss: 0.6922
Epoch 1/1... Discriminator Loss: 1.4061... Generator Loss: 0.6941
Epoch 1/1... Discriminator Loss: 1.3682... Generator Loss: 0.7025
Epoch 1/1... Discriminator Loss: 1.4259... Generator Loss: 0.6889
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7078
Epoch 1/1... Discriminator Loss: 1.3872... Generator Loss: 0.7548
Epoch 1/1... Discriminator Loss: 1.3993... Generator Loss: 0.6807
Epoch 1/1... Discriminator Loss: 1.3854... Generator Loss: 0.6853
Epoch 1/1... Discriminator Loss: 1.4041... Generator Loss: 0.7131
Epoch 1/1... Discriminator Loss: 1.3967... Generator Loss: 0.6975
Epoch 1/1... Discriminator Loss: 1.4098... Generator Loss: 0.6774
Epoch 1/1... Discriminator Loss: 1.4134... Generator Loss: 0.7085
Epoch 1/1... Discriminator Loss: 1.4259... Generator Loss: 0.6988
Epoch 1/1... Discriminator Loss: 1.4330... Generator Loss: 0.6926
Epoch 1/1... Discriminator Loss: 1.4240... Generator Loss: 0.6615
Epoch 1/1... Discriminator Loss: 1.3973... Generator Loss: 0.6827
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.6703
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.7044
Epoch 1/1... Discriminator Loss: 1.3943... Generator Loss: 0.7168
Epoch 1/1... Discriminator Loss: 1.3757... Generator Loss: 0.6998
Epoch 1/1... Discriminator Loss: 1.4068... Generator Loss: 0.6835
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.7009
Epoch 1/1... Discriminator Loss: 1.3852... Generator Loss: 0.6725
Epoch 1/1... Discriminator Loss: 1.3729... Generator Loss: 0.6898
Epoch 1/1... Discriminator Loss: 1.3822... Generator Loss: 0.7190
Epoch 1/1... Discriminator Loss: 1.4032... Generator Loss: 0.6659
Epoch 1/1... Discriminator Loss: 1.4254... Generator Loss: 0.6703
Epoch 1/1... Discriminator Loss: 1.4120... Generator Loss: 0.6739
Epoch 1/1... Discriminator Loss: 1.4026... Generator Loss: 0.6782
Epoch 1/1... Discriminator Loss: 1.3674... Generator Loss: 0.6770
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.6858
Epoch 1/1... Discriminator Loss: 1.3984... Generator Loss: 0.7035
Epoch 1/1... Discriminator Loss: 1.3954... Generator Loss: 0.7052
Epoch 1/1... Discriminator Loss: 1.4044... Generator Loss: 0.6934
Epoch 1/1... Discriminator Loss: 1.3911... Generator Loss: 0.6850
Epoch 1/1... Discriminator Loss: 1.3988... Generator Loss: 0.7051
Epoch 1/1... Discriminator Loss: 1.3885... Generator Loss: 0.6749
Epoch 1/1... Discriminator Loss: 1.3986... Generator Loss: 0.6923
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6880
Epoch 1/1... Discriminator Loss: 1.3860... Generator Loss: 0.7262
Epoch 1/1... Discriminator Loss: 1.3961... Generator Loss: 0.7103
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6917
Epoch 1/1... Discriminator Loss: 1.4117... Generator Loss: 0.6696
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.7072
Epoch 1/1... Discriminator Loss: 1.4022... Generator Loss: 0.7078
Epoch 1/1... Discriminator Loss: 1.3872... Generator Loss: 0.7027
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.6914
Epoch 1/1... Discriminator Loss: 1.3657... Generator Loss: 0.7036
Epoch 1/1... Discriminator Loss: 1.3798... Generator Loss: 0.6998
Epoch 1/1... Discriminator Loss: 1.3831... Generator Loss: 0.6982
Epoch 1/1... Discriminator Loss: 1.3838... Generator Loss: 0.7015
Epoch 1/1... Discriminator Loss: 1.4087... Generator Loss: 0.6809
Epoch 1/1... Discriminator Loss: 1.3958... Generator Loss: 0.7317
Epoch 1/1... Discriminator Loss: 1.3964... Generator Loss: 0.6982
Epoch 1/1... Discriminator Loss: 1.3631... Generator Loss: 0.6735
Epoch 1/1... Discriminator Loss: 1.3683... Generator Loss: 0.6990
Epoch 1/1... Discriminator Loss: 1.3825... Generator Loss: 0.7043
Epoch 1/1... Discriminator Loss: 1.3805... Generator Loss: 0.6664
Epoch 1/1... Discriminator Loss: 1.3616... Generator Loss: 0.7067
Epoch 1/1... Discriminator Loss: 1.3754... Generator Loss: 0.7075
Epoch 1/1... Discriminator Loss: 1.3578... Generator Loss: 0.7171
Epoch 1/1... Discriminator Loss: 1.3902... Generator Loss: 0.6842
Epoch 1/1... Discriminator Loss: 1.4012... Generator Loss: 0.6716
Epoch 1/1... Discriminator Loss: 1.3920... Generator Loss: 0.6811
Epoch 1/1... Discriminator Loss: 1.3887... Generator Loss: 0.6999
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.6711
Epoch 1/1... Discriminator Loss: 1.4226... Generator Loss: 0.6640
Epoch 1/1... Discriminator Loss: 1.4149... Generator Loss: 0.6523
Epoch 1/1... Discriminator Loss: 1.4168... Generator Loss: 0.6748
Epoch 1/1... Discriminator Loss: 1.3963... Generator Loss: 0.6963
Epoch 1/1... Discriminator Loss: 1.3983... Generator Loss: 0.6704
Epoch 1/1... Discriminator Loss: 1.3736... Generator Loss: 0.6971
Epoch 1/1... Discriminator Loss: 1.3733... Generator Loss: 0.7326
Epoch 1/1... Discriminator Loss: 1.3959... Generator Loss: 0.6641
Epoch 1/1... Discriminator Loss: 1.3910... Generator Loss: 0.6991
Epoch 1/1... Discriminator Loss: 1.3853... Generator Loss: 0.6860
Epoch 1/1... Discriminator Loss: 1.3943... Generator Loss: 0.6941
Epoch 1/1... Discriminator Loss: 1.4205... Generator Loss: 0.6997
Epoch 1/1... Discriminator Loss: 1.3866... Generator Loss: 0.6925
Epoch 1/1... Discriminator Loss: 1.4037... Generator Loss: 0.6962
Epoch 1/1... Discriminator Loss: 1.3808... Generator Loss: 0.6771
Epoch 1/1... Discriminator Loss: 1.4130... Generator Loss: 0.7092
Epoch 1/1... Discriminator Loss: 1.3796... Generator Loss: 0.7070
Epoch 1/1... Discriminator Loss: 1.4000... Generator Loss: 0.6945
Epoch 1/1... Discriminator Loss: 1.3926... Generator Loss: 0.7008
Epoch 1/1... Discriminator Loss: 1.4283... Generator Loss: 0.6759
Epoch 1/1... Discriminator Loss: 1.3910... Generator Loss: 0.6757
Epoch 1/1... Discriminator Loss: 1.4418... Generator Loss: 0.6667
Epoch 1/1... Discriminator Loss: 1.4189... Generator Loss: 0.6946
Epoch 1/1... Discriminator Loss: 1.3947... Generator Loss: 0.6749
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.6878
Epoch 1/1... Discriminator Loss: 1.3865... Generator Loss: 0.6666
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.6951
Epoch 1/1... Discriminator Loss: 1.4045... Generator Loss: 0.7283
Epoch 1/1... Discriminator Loss: 1.3845... Generator Loss: 0.6699
Epoch 1/1... Discriminator Loss: 1.3698... Generator Loss: 0.7343
Epoch 1/1... Discriminator Loss: 1.4016... Generator Loss: 0.7101
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.7086
Epoch 1/1... Discriminator Loss: 1.3712... Generator Loss: 0.6737
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.6911
Epoch 1/1... Discriminator Loss: 1.4139... Generator Loss: 0.6875
Epoch 1/1... Discriminator Loss: 1.4077... Generator Loss: 0.6973
Epoch 1/1... Discriminator Loss: 1.3694... Generator Loss: 0.7330
Epoch 1/1... Discriminator Loss: 1.3996... Generator Loss: 0.7036
Epoch 1/1... Discriminator Loss: 1.3872... Generator Loss: 0.6780
Epoch 1/1... Discriminator Loss: 1.3761... Generator Loss: 0.7089
Epoch 1/1... Discriminator Loss: 1.3763... Generator Loss: 0.7031
Epoch 1/1... Discriminator Loss: 1.3725... Generator Loss: 0.7219
Epoch 1/1... Discriminator Loss: 1.3766... Generator Loss: 0.7103
Epoch 1/1... Discriminator Loss: 1.4240... Generator Loss: 0.6860
Epoch 1/1... Discriminator Loss: 1.4010... Generator Loss: 0.7156
Epoch 1/1... Discriminator Loss: 1.3982... Generator Loss: 0.6788
Epoch 1/1... Discriminator Loss: 1.3620... Generator Loss: 0.7175
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.6822
Epoch 1/1... Discriminator Loss: 1.3893... Generator Loss: 0.7085
Epoch 1/1... Discriminator Loss: 1.3950... Generator Loss: 0.6882
Epoch 1/1... Discriminator Loss: 1.4054... Generator Loss: 0.6699
Epoch 1/1... Discriminator Loss: 1.4045... Generator Loss: 0.7081
Epoch 1/1... Discriminator Loss: 1.3935... Generator Loss: 0.7042
Epoch 1/1... Discriminator Loss: 1.3932... Generator Loss: 0.6630
Epoch 1/1... Discriminator Loss: 1.3900... Generator Loss: 0.6991
Epoch 1/1... Discriminator Loss: 1.4363... Generator Loss: 0.6912
Epoch 1/1... Discriminator Loss: 1.3928... Generator Loss: 0.6930
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.6799
Epoch 1/1... Discriminator Loss: 1.3756... Generator Loss: 0.6866
Epoch 1/1... Discriminator Loss: 1.3938... Generator Loss: 0.7056
Epoch 1/1... Discriminator Loss: 1.4346... Generator Loss: 0.6963
Epoch 1/1... Discriminator Loss: 1.3900... Generator Loss: 0.6554
Epoch 1/1... Discriminator Loss: 1.4076... Generator Loss: 0.6944
Epoch 1/1... Discriminator Loss: 1.4070... Generator Loss: 0.7003
Epoch 1/1... Discriminator Loss: 1.3914... Generator Loss: 0.6697
Epoch 1/1... Discriminator Loss: 1.3696... Generator Loss: 0.7034
Epoch 1/1... Discriminator Loss: 1.4439... Generator Loss: 0.7015
Epoch 1/1... Discriminator Loss: 1.3981... Generator Loss: 0.7431
Epoch 1/1... Discriminator Loss: 1.3894... Generator Loss: 0.6939
Epoch 1/1... Discriminator Loss: 1.3958... Generator Loss: 0.7006
Epoch 1/1... Discriminator Loss: 1.3700... Generator Loss: 0.7035
Epoch 1/1... Discriminator Loss: 1.3891... Generator Loss: 0.6949
Epoch 1/1... Discriminator Loss: 1.3804... Generator Loss: 0.7234
Epoch 1/1... Discriminator Loss: 1.3645... Generator Loss: 0.6795
Epoch 1/1... Discriminator Loss: 1.3952... Generator Loss: 0.6852
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.6821
Epoch 1/1... Discriminator Loss: 1.3994... Generator Loss: 0.6817
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6791
Epoch 1/1... Discriminator Loss: 1.3867... Generator Loss: 0.7201
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.6789
Epoch 1/1... Discriminator Loss: 1.4324... Generator Loss: 0.6631
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.6812
Epoch 1/1... Discriminator Loss: 1.3791... Generator Loss: 0.7032
Epoch 1/1... Discriminator Loss: 1.3867... Generator Loss: 0.6788
Epoch 1/1... Discriminator Loss: 1.4326... Generator Loss: 0.6565
Epoch 1/1... Discriminator Loss: 1.4392... Generator Loss: 0.6745
Epoch 1/1... Discriminator Loss: 1.3993... Generator Loss: 0.7109
Epoch 1/1... Discriminator Loss: 1.3787... Generator Loss: 0.7233
Epoch 1/1... Discriminator Loss: 1.3704... Generator Loss: 0.6928
Epoch 1/1... Discriminator Loss: 1.4109... Generator Loss: 0.6815
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7014
Epoch 1/1... Discriminator Loss: 1.4005... Generator Loss: 0.6612
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.6978
Epoch 1/1... Discriminator Loss: 1.3937... Generator Loss: 0.7077
Epoch 1/1... Discriminator Loss: 1.3921... Generator Loss: 0.6999
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.6908
Epoch 1/1... Discriminator Loss: 1.3903... Generator Loss: 0.6994
Epoch 1/1... Discriminator Loss: 1.3942... Generator Loss: 0.7326
Epoch 1/1... Discriminator Loss: 1.3786... Generator Loss: 0.6658
Epoch 1/1... Discriminator Loss: 1.3918... Generator Loss: 0.7039
Epoch 1/1... Discriminator Loss: 1.3582... Generator Loss: 0.7357
Epoch 1/1... Discriminator Loss: 1.3853... Generator Loss: 0.7007
Epoch 1/1... Discriminator Loss: 1.4066... Generator Loss: 0.6688
Epoch 1/1... Discriminator Loss: 1.4074... Generator Loss: 0.6969
Epoch 1/1... Discriminator Loss: 1.3718... Generator Loss: 0.7065
Epoch 1/1... Discriminator Loss: 1.3728... Generator Loss: 0.6825
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.6739
Epoch 1/1... Discriminator Loss: 1.4050... Generator Loss: 0.6983
Epoch 1/1... Discriminator Loss: 1.3892... Generator Loss: 0.6750
Epoch 1/1... Discriminator Loss: 1.3891... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.3798... Generator Loss: 0.6799
Epoch 1/1... Discriminator Loss: 1.4134... Generator Loss: 0.6912
Epoch 1/1... Discriminator Loss: 1.3714... Generator Loss: 0.7208
Epoch 1/1... Discriminator Loss: 1.3815... Generator Loss: 0.7057
Epoch 1/1... Discriminator Loss: 1.4144... Generator Loss: 0.6807
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.6904
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6675
Epoch 1/1... Discriminator Loss: 1.3845... Generator Loss: 0.7236
Epoch 1/1... Discriminator Loss: 1.3956... Generator Loss: 0.6798
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.7044
Epoch 1/1... Discriminator Loss: 1.3716... Generator Loss: 0.7204
Epoch 1/1... Discriminator Loss: 1.3930... Generator Loss: 0.7069
Epoch 1/1... Discriminator Loss: 1.3891... Generator Loss: 0.7248
Epoch 1/1... Discriminator Loss: 1.3950... Generator Loss: 0.7053
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.6768
Epoch 1/1... Discriminator Loss: 1.3764... Generator Loss: 0.7032
Epoch 1/1... Discriminator Loss: 1.3871... Generator Loss: 0.7092
Epoch 1/1... Discriminator Loss: 1.4020... Generator Loss: 0.7146
Epoch 1/1... Discriminator Loss: 1.4144... Generator Loss: 0.6911
Epoch 1/1... Discriminator Loss: 1.4170... Generator Loss: 0.6969
Epoch 1/1... Discriminator Loss: 1.4100... Generator Loss: 0.6812
Epoch 1/1... Discriminator Loss: 1.3716... Generator Loss: 0.6988
Epoch 1/1... Discriminator Loss: 1.3582... Generator Loss: 0.7137
Epoch 1/1... Discriminator Loss: 1.4109... Generator Loss: 0.7046
Epoch 1/1... Discriminator Loss: 1.3552... Generator Loss: 0.7084
Epoch 1/1... Discriminator Loss: 1.3792... Generator Loss: 0.6984
Epoch 1/1... Discriminator Loss: 1.4089... Generator Loss: 0.6949
Epoch 1/1... Discriminator Loss: 1.4043... Generator Loss: 0.6935
Epoch 1/1... Discriminator Loss: 1.3806... Generator Loss: 0.7082
Epoch 1/1... Discriminator Loss: 1.3721... Generator Loss: 0.7060
Epoch 1/1... Discriminator Loss: 1.3878... Generator Loss: 0.6958
Epoch 1/1... Discriminator Loss: 1.3948... Generator Loss: 0.6804
Epoch 1/1... Discriminator Loss: 1.3980... Generator Loss: 0.6901
Epoch 1/1... Discriminator Loss: 1.4008... Generator Loss: 0.7012
Epoch 1/1... Discriminator Loss: 1.3896... Generator Loss: 0.6874
Epoch 1/1... Discriminator Loss: 1.3793... Generator Loss: 0.7048
Epoch 1/1... Discriminator Loss: 1.4092... Generator Loss: 0.7009
Epoch 1/1... Discriminator Loss: 1.3838... Generator Loss: 0.6973
Epoch 1/1... Discriminator Loss: 1.4104... Generator Loss: 0.6718
Epoch 1/1... Discriminator Loss: 1.4054... Generator Loss: 0.6919
Epoch 1/1... Discriminator Loss: 1.4300... Generator Loss: 0.6768
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.6974
Epoch 1/1... Discriminator Loss: 1.3952... Generator Loss: 0.7071
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.7171
Epoch 1/1... Discriminator Loss: 1.3986... Generator Loss: 0.7290
Epoch 1/1... Discriminator Loss: 1.3858... Generator Loss: 0.6831
Epoch 1/1... Discriminator Loss: 1.3921... Generator Loss: 0.6921
Epoch 1/1... Discriminator Loss: 1.3885... Generator Loss: 0.6978
Epoch 1/1... Discriminator Loss: 1.3817... Generator Loss: 0.6809
Epoch 1/1... Discriminator Loss: 1.3741... Generator Loss: 0.7071
Epoch 1/1... Discriminator Loss: 1.3914... Generator Loss: 0.7005
Epoch 1/1... Discriminator Loss: 1.4008... Generator Loss: 0.6876
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.6867
Epoch 1/1... Discriminator Loss: 1.3880... Generator Loss: 0.6874
Epoch 1/1... Discriminator Loss: 1.3895... Generator Loss: 0.6781
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.6855
Epoch 1/1... Discriminator Loss: 1.3793... Generator Loss: 0.6845
Epoch 1/1... Discriminator Loss: 1.3898... Generator Loss: 0.6894
Epoch 1/1... Discriminator Loss: 1.3855... Generator Loss: 0.6945
Epoch 1/1... Discriminator Loss: 1.3973... Generator Loss: 0.6690
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.6788
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.7009
Epoch 1/1... Discriminator Loss: 1.3927... Generator Loss: 0.7096
Epoch 1/1... Discriminator Loss: 1.4057... Generator Loss: 0.6801
Epoch 1/1... Discriminator Loss: 1.3877... Generator Loss: 0.7089
Epoch 1/1... Discriminator Loss: 1.3686... Generator Loss: 0.7041
Epoch 1/1... Discriminator Loss: 1.4179... Generator Loss: 0.6724
Epoch 1/1... Discriminator Loss: 1.3957... Generator Loss: 0.6884
Epoch 1/1... Discriminator Loss: 1.3992... Generator Loss: 0.6805
Epoch 1/1... Discriminator Loss: 1.3840... Generator Loss: 0.6928
Epoch 1/1... Discriminator Loss: 1.4062... Generator Loss: 0.6982
Epoch 1/1... Discriminator Loss: 1.3902... Generator Loss: 0.6904
Epoch 1/1... Discriminator Loss: 1.3881... Generator Loss: 0.6809
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.6987
Epoch 1/1... Discriminator Loss: 1.3970... Generator Loss: 0.6922
Epoch 1/1... Discriminator Loss: 1.3860... Generator Loss: 0.7000
Epoch 1/1... Discriminator Loss: 1.3898... Generator Loss: 0.7054
Epoch 1/1... Discriminator Loss: 1.3951... Generator Loss: 0.6867
Epoch 1/1... Discriminator Loss: 1.3929... Generator Loss: 0.7004
Epoch 1/1... Discriminator Loss: 1.3745... Generator Loss: 0.6896
Epoch 1/1... Discriminator Loss: 1.4009... Generator Loss: 0.7011
Epoch 1/1... Discriminator Loss: 1.3987... Generator Loss: 0.7079
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7290
Epoch 1/1... Discriminator Loss: 1.4001... Generator Loss: 0.6767
Epoch 1/1... Discriminator Loss: 1.3709... Generator Loss: 0.6989
Epoch 1/1... Discriminator Loss: 1.3838... Generator Loss: 0.6919
Epoch 1/1... Discriminator Loss: 1.4162... Generator Loss: 0.6769
Epoch 1/1... Discriminator Loss: 1.3875... Generator Loss: 0.6976
Epoch 1/1... Discriminator Loss: 1.3754... Generator Loss: 0.6891
Epoch 1/1... Discriminator Loss: 1.4357... Generator Loss: 0.6477
Epoch 1/1... Discriminator Loss: 1.4087... Generator Loss: 0.6904
Epoch 1/1... Discriminator Loss: 1.3954... Generator Loss: 0.6819
Epoch 1/1... Discriminator Loss: 1.3948... Generator Loss: 0.7026
Epoch 1/1... Discriminator Loss: 1.4060... Generator Loss: 0.6850
Epoch 1/1... Discriminator Loss: 1.4071... Generator Loss: 0.6826
Epoch 1/1... Discriminator Loss: 1.3606... Generator Loss: 0.6971

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.